Variational Weakly Supervised Sentiment Analysis with Posterior Regularization (2021.eacl-main)
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| Challenge: | Existing methods for sentiment analysis require human annotations, but they are scarce. |
| Approach: | They propose a posterior regularization framework to control the posterior distribution of label assignment. |
| Outcome: | The proposed framework improves the variational approach to the weakly supervised sentiment analysis and the performance is more stable with smaller prediction variance. |
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| Challenge: | Existing work that improves document-level sentiment analysis by encoding user and product information has been limited to considering only the text of the current review. |
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